Using directional curvatures to visualize folding patterns of the GTM projection manifolds

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Abstract

In data visualization, characterizing local geometric properties of non-linear projection manifolds provides the user with valuable additional information that can influence further steps in the data analysis. We take advantage of the smooth character of GTM projection manifold and analytically calculate its local directional curvatures. Curvature plots are useful for detecting regions where geometry is distorted, for changing the amount of regularization in non-linear projection manifolds, and for choosing regions of interest when constructing detailed lower-level visualization plots.

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Details

Publication date1 Jan 2001
Publication titleArtificial Neural Networks — ICANN 2001
EditorsG. Dorffner, H. Bischof, K. Hornik.
PublisherSpringer
Pages421-428
Number of pages8
Volume2130
ISBN (Print)3540424865, 9783540446682
Original languageEnglish
EventInternational Conference on Artificial Neural Networks, ICANN 2001 - Vienna, Austria

Publication series

NameLecture Notes in Computer Science
PublisherSpringer-Verlag

Conference

ConferenceInternational Conference on Artificial Neural Networks, ICANN 2001
CountryAustria
CityVienna
Period21/08/0125/08/01

Bibliographic note

The original publication is available at www.springerlink.com

    Keywords

  • data visualization, non-linear projection manifolds, directional curvatures, curvature plots, geometry, visualization plots

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